A 2-D visual model for Sasang constitution classification based on a fuzzy neural network

Abstract

The human constitution can be classified into four possible constitutions according to an individual's temperament and nature: Tae-Yang, So-Yang, Tae-Eum, and So-Eum. This classification is known as the Sasang constitution. In this study, we classified the four types of Sasang constitutions by measuring twelve sets of meridian energy signals with a Ryodoraku device. We then developed a Sasang constitution classification method based on a fuzzy neural network (FNN) and a two-dimensional (2-D) visual model. We obtained meridian energy signals from 35 subjects for the So-Yang, Tae-Eum, and So-Eum constitutions. A FNN was used to obtain defuzzification values for the 2-D visual model, which was then applied to the classification of these three Sasang constitutions. Finally, we achieved a Sasang constitution recognition rate of 89.4 %. © 2013 Springer Science+Business Media.